The decline in postural balance has a negative impact on the performance of functional tasks in individuals with Parkinson's Disease.

INTRODUCTION: An accurate assessment of balance problems is critical for decreasing the risk of falling in patients with Parkinson's Disease (PD). Reliable diagnostic tools such as Computerized Dynamic Posturography (CDP) are not feasible for the clinical setting. Therefore, the present study's aim was to assess the correlation between the clinical Balance Evaluation Systems Test (BESTest) and CDP. METHODS: 20 male older adults with Parkinson's Disease (PD) were included in this study. Participants first executed the Sit-To-Stand (STS), Step/Quick turn (SQT), and Step Up and Over (SUO) tests on a Balance Master® force platform, followed by a clinical balance evaluation using the BESTest. RESULTS: Four outcomes of the CDP were negatively correlated with one or more BESTest domains or total BESTest score: STS sway velocity was negatively correlated with the anticipatory postural adjustment (p = 0.02) and sensory orientation (p = 0.01) domains. SQT turn time was negatively correlated with biomechanical restriction (for turns to the left, p = 0.01, and right, p = 0.03, respectively), postural response (p = 0.01, p = 0.01), dynamic balance during gait (p = 0.007, p = 0.001), and total score (p = 0.02, p = 0.01). Step over time to the right in SUP was negatively correlated with the limits of the stability domain (p = 0.002) and total BESTest score (p = 0.020). SUO impact index was negatively correlated with the anticipatory postural adjustment domain (p = 0.01). CONCLUSION: This study shows that several BESTest domains are significantly correlated with CDP outcomes, demonstrating that the BESTest can be used as a more clinically feasible alternative for computerized posturography, without loss of information.

Optimization Reduces Knee-Joint Forces During Walking and Squatting: Validating the Inverse Dynamics Approach for Full Body Movements on Instrumented Knee Prostheses.

Because of the redundancy of our motor system, movements can be performed in many ways. While multiple motor control strategies can all lead to the desired behavior, they result in different joint and muscle forces. This creates opportunities to explore this redundancy, for example, for pain avoidance or reducing the risk of further injury. To assess the effect of different motor control optimization strategies, a direct measurement of muscle and joint forces is desirable, but problematic for medical and ethical reasons. Computational modeling might provide a solution by calculating approximations of these forces. In this study, we used a full-body computational musculoskeletal model to (a) predict forces measured in knee prostheses during walking and squatting and (b) study the effect of different motor control strategies (i.e., minimizing joint force vs. muscle activation) on the joint load and prediction error. We found that musculoskeletal models can accurately predict knee joint forces with a root mean squared error of <0.5 body weight (BW) in the superior direction and about 0.1 BW in the medial and anterior directions. Generally, minimization of joint forces produced the best predictions. Furthermore, minimizing muscle activation resulted in maximum knee forces of about 4 BW for walking and 2.5 BW for squatting. Minimizing joint forces resulted in maximum knee forces of 2.25 BW and 2.12 BW, that is, a reduction of 44% and 15%, respectively. Thus, changing the muscular coordination strategy can strongly affect knee joint forces. Patients with a knee prosthesis may adapt their neuromuscular activation to reduce joint forces during locomotion.

Influence of arm swing on cost of transport during walking.

Normal arm swing plays a role in decreasing the cost of transport during walking. However, whether excessive arm swing can reduce the cost of transport even further is unknown. Therefore, we tested the effects of normal and exaggerated arm swing on the cost of transport in the current study. Healthy participants (n=12) walked on a treadmill (1.25 m/s) in seven trials with different arm swing amplitudes (in-phase, passive restricted, active restricted, normal, three gradations of extra arm swing), while metabolic energy cost and the vertical angular momentum (VAM) and ground reaction moment (GRM) were measured. In general, VAM and GRM decreased as arm swing amplitude was increased, except for in the largest arm swing amplitude condition. The decreases in VAM and GRM were accompanied by a decrease in cost of transport from in-phase walking (negative amplitude) up to a slightly increased arm swing (non-significant difference compared to normal arm swing). The most excessive arm swings led to an increase in the cost of transport, most likely due to the cost of swinging the arms. In conclusion, increasing arm swing amplitude leads to a reduction in VAM and GRM, but it does not lead to a reduction in cost of transport for the most excessive arm swing amplitudes. Normal or slightly increased arm swing amplitude appear to be optimal in terms of cost of transport in young and healthy individuals.This article has an associated First Person interview with the first author of the paper.